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Prediction mode grouping and coding bits grouping based on texture complexity for Fast HEVC intra-coding

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Abstract

HEVC (High Efficiency Video Coding) as one of the newest international video coding standard, can achieve about 50% bit rate reduction compared with H.264/AVC (Advanced Video Coding) with the same perceptual quality by the use of flexible CTU (coding tree unit) structure, but at the same time, it also dramatically adds its computational complexity for HEVC. To reduce the computational complexity, a fast intra-prediction mode and CU (Coding Unit) size decision algorithm based on prediction mode and coding bits grouping is presented for HEVC intra-encoding in this paper. The contribution of this paper lies in the fact that we successfully use the prediction mode grouping and coding bits grouping technologies to rapidly realize the optimal prediction mode and size decision for the current CU, thus saving much computation complexity for HEVC. Specifically, in our scheme, first, we use grouping technology to group 35 intra-prediction modes into 5 subsets of candidate modes list according to the texture complexity of current PU (Prediction Unit), and each subset only contains 11 intra-prediction modes, which can greatly reduce the traversing and calculating number of candidate mode in RMD (Rough Mode Decision); second, we use coding bits grouping technology to quickly judge whether the current CU needs to be further divided on the basis of the studying of texture complexity in the current CU, which can reduce many unnecessary prediction and partition operations for the current CU; at last we use the fast intra-mode prediction and CU size decision algorithm above to quickly realize the optimal encoding for the current CU in HEVC. As a result, the high computational complexity in HEVC intra-encoding can be efficiently reduced by our proposed scheme. And the simulation results of our experiments show that our proposed fast intra-coding algorithm based on prediction mode and coding bit grouping in this paper can reduce about 49.10% computational complexity on average only at a cost of 0.92% bit rate increase and 0.065 db PSNR decline compared with the standard reference HM16.1algorithm under all-intra-configuration.

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Acknowledgements

Bang Ji contributed equally to this work and is considered co-first authors. The work was supported by the National Natural Science Foundation of China (No. 61602187) and (No. 6180405); the National Key Research and Development Plan (No. 2016YFD0200700); the Guangdong Science and Technology Projects (No. 2019B020219002) and Guangdong Laboratory of Lingnan Modern Agriculture.

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Authors and Affiliations

  1. College of Electronic Engineering, South China Agricultural University, Guangzhou, 510642, China

    Jianhua Wang, Bang Ji & Haozhan Wang

  2. School of Computer Science and Engineering, Nanyang Technological University, Singapore, 639798, Singapore

    Jianhua Wang

  3. National Center for International Collaboration Research on Precision Agricultural Aviation, Guangzhou, 510642, China

    Jianhua Wang

  4. Faculty of Automation, Guangdong University of Technology, Guangzhou, 510005, China

    Lianglun Cheng

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  1. Jianhua Wang
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Correspondence to Jianhua Wang.

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Wang, J., Ji, B., Wang, H. et al. Prediction mode grouping and coding bits grouping based on texture complexity for Fast HEVC intra-coding. J Real-Time Image Proc 18, 839–856 (2021). https://doi.org/10.1007/s11554-020-01034-2

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